This was an interesting one. Looking at the dataset, my first thought was to visualise deaths by country (of course!). So I plotted all the countries, but noticed that there were no reported deaths for North America, Europe, Australia, New Zealand, etc. How did I know? It literally took 2 seconds once I opened Tableau: double click on ‘Country’ and look at the result:

This led to my second step: Let’s group the countries into regions, because heat maps have been done before :-):

I used the map options menu to visually group the countries from the above map by dragging across the dots and naming the aliases accordingly. This took 2 minutes:

Next I built a bar chart to compare the total deaths across these different regions:

Very interesting and probably expected, but the viz isn’t great because African countries basically need a different scale, but using independent scales would skew the results, so let’s look for a different solution.

Maybe I should just group all Non-African countries and compare them to Africa?

Yeah getting better but I still think this isn’t that great.
What I like about this viz, however, is that it shows a general trend for non-African countries to reduce their Malaria deaths while African countries seem to still struggle to address and contain the disease.

Next up I was interested in what individual countries drive the results in Africa and this is where things got interesting and I found a whole new story to what I had originally planned…

What I noticed was that malaria deaths in the Democratic Republic of Congo have increased over the years rather than reducing like you would expect given medical advances etc.

This can best be seen on the following dashboards which shows small multiples:

Those quick and eagle-eyed readers among you have probably noticed a reverse trend in another country. What’s going on in Kenya?

Malaria deaths in Kenya seem to be going down.

Instead of trying to come up with a great viz about Malaria deaths across the world, these findings, which occurred in a matter of minutes thanks to Tableau’s intuitive interface and the inquisitive analysis this enables, I decided that I wanted to tell a story about Kenya and the Democratic Republic of Congo…

The data was put together fairly quickly, the formatting took a little while to get right :-). This seems to be the usual way things go hehe.

The final dashboard shows a story in three different visualisations:

The first charts indicates that there is actually some missing data for Kenya but the overall trend is in the right direction and Malaria deaths are going down. The Democratic Republic of Congo, however, is showing the reverse trend.

The second chart uses bars to show the same picture and I find the Kenyan data from 2011 onward even more strikingly obvious than in the line chart.

Finally I manually created a sort of highlight table for both countries. I wanted to show the actual numbers for each year as well as a bar. But I also wanted the shading of the colour to correspond to the number of deaths. This forced me to use the standard colour palette which Tableau applies automatically. I had to duplicate my ‘Deaths’ measure and turn the copy into a dimension. I then applied both the ‘Deaths’ dimension and the country dimension on colour simultaneously and sorted the ‘Deaths’ dimension in descending order, reapplied the colour and got the following result:

I’m happy with the final result but I felt it is important to tell the whole story of how this dashboard came about because it so clearly highlights what Tableau helps you to do: Look at and understand your data, find a story and probably a lot more insights once you drag, drop and investigate…